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In recent years, numerous biocomputational tools have been designed to extract functional and evolutionary information from multiple sequence alignments (MSAs) of proteins and genes. Most biologists working actively on the characterization of proteins from a single or family perspective use the MSA analysis to retrieve valuable information about amino acid conservation and the functional role of residues in query protein(s). In MSAs, adjustment of alignment parameters is a key point to improve the quality of MSA output. However, this issue is frequently underestimated and/or misunderstood by scientists and there is no in-depth knowledge available in this field. This brief review focuses on biocomputational approaches complementary to MSA to help distinguish functional residues in protein families. These additional analyses involve issues ranging from phylogenetic to statistical, which address the detection of amino acids pivotal for protein function at any level. In recent years, a large number of tools has been designed for this very purpose. Using some of these relevant, useful tools, we have designed a practical pipeline to perform in silico studies with a view to improving the characterization of family proteins and their functional residues. This review-guide aims to present biologists a set of specially designed tools to study proteins. These tools are user-friendly as they use web servers or easy-to-handle applications. Such criteria are essential for this review as most of the biologists (experimentalists) working in this field are unfamiliar with these biocomputational analysis approaches.

Bioinformatics emerged about 50 years ago, but it was developed greatly during the early 1980s by robust databases such as GenBank, EMBL, and DNA Database of Japan (DDBJ). Bioinformatic routines were rapidly adapted once the main algorithms for sequence analysis became available worldwide. As in other science fields, bioinformatics had minimal impact in low-income countries of Latin America until the last decade. We revised the bioinformatics state of art in Colombia and found a few bioinformatics groups carrying out basic computational biology research. Nowadays, bioinformatics in Colombia has a hopeful scenario thanks to recent science policies adopted by the Colombian Government. Such policies have been adopted in order to establish a new model of sustainable scientific research. In this brief report we revise the bioinformatics state of the art in Colombia. Finally, we conclude with some considerations for the proposed science model and we describe different perspectives of interest for the Colombian scientific community.

The Receptor Activity-Modifying Proteins (RAMP) is a family constituted by a single N-terminal extracellular domain and a transmembrane region ending in a short cytoplasmic region. Due to their specific role in modulating the specificity of ligand binding in many class II G-Protein Coupled Receptors, these proteins are awaiting further characterization and elucidation of their structure. This was the aim of this study. We were able to find 13 new RAMP sequences including new protein sequences and predicted peptides from Expressed Sequence Tags and genomic DNA, all of them annotated in databases such as GeneBank, EMBL, Swissprot and ENSEMBL. The predicted peptides came from an array of different organisms including Teleostei and Elasmobranchii species, of which the latter was the most ancient RAMP sequence found. It was also possible to efficiently predict the 1D structure of the extracellular RAMP domain and its 3D conformation was inferred through a combination of bioinformatic approaches such as threading. The 1D structure of the extracellular RAMP domain was predicted as three α-helix domain. The most highly conserved residues in the RAMP family were found to be involved in critical functions. Bioinformatic data mining and multiple sequence alignment analysis were crucial for improving the characterization of RAMP proteins and prediction of their 1D and 3D configurations. [ABSTRACT FROM AUTHOR]